In this episode, I'm sitting down with Kit Cox, Founder & CTO of Enate, exploring Kit's journey from a young coder (BBC Basic anyone?) to the founder of a workflow automation platform.

We discuss the evolution of Enate, its applications in service delivery, and real-world use cases, particularly in the B2B sector.

Kit explains how Enate helps organizations operationalize AI, improve customer experiences, and drive business growth. Our conversation highlights the importance of sentiment analysis and the need for organizations to adapt to new technologies to remain competitive.

Chapters

• 00:00 Introduction to Conversational AI and Innate AI
• 00:09 Kit's Journey: From Coding to AI Solutions
• 04:01 Understanding Innate AI's Workflow Platform
• 08:08 Real-World Applications: Case Study of TMF
• 12:16 The Role of AI in Service Delivery
• 15:57 Extensibility and Integration of Innate AI
• 16:00 Innovative Use Cases and Customer Success Stories
• 24:14 Operationalizing AI in Business
• 26:33 Deployment Strategies for Innate AI

In today's episode, we're meeting ⁠Darren Ford⁠, the Founder and Director of ⁠The CAI Company⁠.

Darren and his team are amongst the most experienced Conversational AI experts around, having driven the strategies and implementations for some of the largest players around.

Our discussion is wide-ranging. We start first with Darren's background and the origin story of ⁠The CAI Company⁠. Then we get into some key use cases, he talks about how consumer acceptance is really changing (for the positive) and he highlights some of the key requirements for any successful implementation -- namely, executive sponsorship and commitment, data-led decision making and the importance of talent development.

Reach out to Darren ⁠at his company website⁠ or ⁠via his LinkedIn Profile⁠.

Chapters

• 00:00 Introduction to Conversational AI and CAI Company
• 02:47 Darren's Background and the Origin of CAI Company
• 04:10 Use Cases and Growth of Conversational AI
• 10:08 Consumer Acceptance and Chatbot Horror Stories
• 12:30 Generative AI and Executive Awareness
• 15:48 Talent Development in Conversational AI
• 18:44 Ethics in Conversational AI
• 20:59 Internal vs External Chatbots
• 23:46 Key Considerations for Executives in Conversational AI

Keywords

Conversational AI, CAI Company, chatbot, generative AI, voice technology, user experience, ethics, talent development, executive awareness, use cases

In today's episode, I'm speaking with Ellen Keenan-O'Malley, a commercial IP lawyer at EIP, about the legal challenges surrounding Artificial Intelligence and Conversational AI.

We discuss the current state of AI law, the implications of GDPR on Conversational AI, and the importance of understanding liability in AI solutions.

Ellen emphasizes the need for companies to consider legal aspects from the outset of AI development and highlights the evolving role of legal professionals in the tech landscape.

If you've got any questions around the topic of intellectual property and AI, I would strongly recommend reaching out to Ellen for a conversation via her corporate profile on EIP.com or her LinkedIn profile.

Takeaways

• AI law is currently ambiguous and evolving.
• Companies often approach lawyers at the last minute.
• Data protection is a significant concern in conversational AI.
• Existing laws like GDPR still apply to AI technologies.
• Indemnity provisions are crucial for AI vendors.
• Legal considerations should be integrated from the start of AI projects.
• Human intervention is necessary to mitigate AI risks.
• AI can enhance efficiency in the legal profession.
• The legal profession must adapt to the rise of AI.
• Engaging with legal experts early can save time and resources.

Chapters

• 00:00 Introduction to AI Legal Issues
• 03:38 Navigating AI Regulations and Compliance
• 08:36 Understanding Liability in AI Implementations
• 11:15 The Role of Legal Professionals in AI Development
• 15:17 Future of AI in the Legal Profession

In this episode, I'm speaking with Neil Marley, CEO of Qualyfi, about askQ, the dedicated AI assistant built for technology delivery and consulting teams.

AskQ is an LLM/RAG-enabled solution that provides 24/7 contextual answers for anyone working in your technology environment - so it's especially useful for consulting and tech delivery teams.

We discuss the evolution of technology delivery, the role of AI in training and development, and the challenges faced by organisations in standardising processes.

Neil shares insights on how Qualyfi aims to democratise knowledge and provide opportunities for individuals from diverse backgrounds to excel in tech delivery. We also explore the future implications of AI on the tech industry and how organisations can leverage these advancements for competitive advantage.

You contact Neil on LinkedIn or via the company's website at qualify.co.uk.

Takeaways

• AI is at a similar maturity stage as the public cloud was in its early days.
• Qualyfi aims to open opportunities for individuals without traditional academic backgrounds.
• The AskQ service combines Qualyfi's IP with an LLM to provide relevant answers to users on demand.
• Training and mentoring are crucial for early career development in tech.
• AI can significantly reduce the time required for tasks like creating statements of work.
• Standardization in tech delivery is essential for efficiency and risk management.
• Qualyfi's approach focuses on empathy and determination in selecting candidates.
• The future of tech delivery will involve smaller teams using software agents.
• Organisations need to adapt their talent acquisition strategies to include AI tools.

Chapters

• 00:00 Introduction and Background
• 00:31 The Rise of Public Cloud and AI
• 02:30 Qualify's Mission and Methodology
• 05:26 The Role of Conversational AI in Training
• 08:22 Humanising the Learning Journey
• 10:47 Challenges in Tech Delivery
• 13:49 Qualify's Service Offerings
• 16:26 The Future of Tech Delivery with AI
• 19:38 Implications of AI on Workforce Dynamics
• 22:40 Navigating the Current AI Landscape
• 25:28 Conclusion and Call to Action

In this episode, I'm meeting Tom Sherwood, CEO of Koios to discuss the bleeding-edge field of emotionally intelligent AI. This is definitely worth a listen.

Tom shares his unique background (the Army, Recruiter, Snap, Spotify!) and then goes on to explain the formation of Koios, and how their technology leverages voice analysis to understand personality traits.

We explore some of the applications of the Koios technology in the recruitment and sales markets, we discuss the business model behind the Koios API, and I ask Tom about the future of human-machine interaction.

Tom finishes by discussing the importance of human connection in AI systems and offers insights for those developing conversational AI interfaces.

If you'd like to know more, I strongly recommend reaching out to Tom directly via his LinkedIn profile.

Takeaways

• Emotionally intelligent AI can enhance human interactions.
• Voice analysis can reveal personality traits effectively.
• Recruitment processes can benefit from personality insights.
• Sales strategies can be tailored based on personality understanding.
• Koios uses acoustic and linguistic data for analysis.
• The business model is based on API calls for analysis.
• Human-machine interaction is evolving with AI advancements.
• Understanding the human element is crucial in AI development.
• AI can help scale coaching and training in organisations.
• Future applications may include personalised virtual coaching.

Chapters

• 00:00 Introduction to Emotionally Intelligent AI
• 02:40 Tom's Unique Background and Journey
• 05:52 The Birth of Koios and Its Mission
• 08:43 Understanding Personality Through Voice
• 11:30 Applications in Recruitment and Sales
• 14:39 Business Model and API Functionality
• 17:33 Ethical Considerations and Use Cases
• 20:46 Future Roadmap and Human-Machine Interaction
• 23:45 Enhancing Conversational AI with Emotional Intelligence
• 26:16 Final Thoughts and Recommendations

In this episode, I sit down with Amelia Lowe⁠, VP Operations at SquareTrade Insurance.

Amelia shares insights on the importance of customer centricity, and how the company is using AI, particularly conversational AI, to improve service delivery throughout their European operations.

She discusses the challenges faced in adopting AI, the leadership perspective on technology implementation, and customer reactions.

Takeaways

• SquareTrade protects a wide range of products, from phones to fridges.
• The company has expanded significantly in Europe over the last nine years.
• Customer expectations are evolving, requiring a more personalised approach.
• AI is critical for achieving customer centricity and enhancing experiences.
• Chatbots are being used to provide seamless customer service.
• Building confidence in AI requires rigorous testing and iteration.
• AI should be viewed as an extension of the team, not just technology.
• Balancing automation with a human touch is essential for customer trust.
• The buy versus build decision for AI solutions often requires a hybrid approach.
• Customer reactions to AI integration can vary based on effectiveness.

Chapters

• 00:00 Introduction and Overview of SquareTrade
• 01:32 The Role of AI in SquareTrade's Success
• 03:14 Radical Customer Centricity and Personalisation
• 05:01 The Importance of AI in Sustainable Growth
• 06:08 Balancing Commercial Objectives and Customer Experience
• 07:48 The Role of Chatbots in Enhancing Customer Service
• 10:31 Building High-Performing Teams in AI Implementation
• 13:35 Buy vs. Build Approach in AI Adoption
• 15:36 Leveraging AI for Multilingual Customer Service
• 16:34 Success Story: Using AI to Improve Customer Service
• 16:34 Challenges in Adopting Conversational AI
• 18:12 Client Response to Augmented Customer Service
• 19:21 How to Connect with Amelia Lowe and SquareTrade

Keywords

SquareTrade, insurance, AI, customer experience, conversational AI, chatbots, B2B2C, customer centricity, technology, leadership

In this episode, I showcase the audio generation capabilities of NotebookLM, a note-taking research assistant powered by Google's Gemini.

To give it a test run, I uploaded a recent article that the team at Nordic FinTech Magazine published for me on the topic of Conversational AI being 'the next interface' in Banking.

Having uploaded the material, I had the option to generate an audio overview.

I did this.

Goodness me it's good.

It's made a mini-podcast or NPR-style audio feature about my article.

I have actually included the audio it generated. The quality is ridiculously good. Have a listen and let me know what you think.

Nice work Google.

In today's episode, Luke Budka, AI Director of Definition, discusses the use of Conversational AI in public relations and communications. He explains how his agency has integrated AI into their services and the benefits it brings to clients. Luke emphasizes the importance of understanding use cases and leveraging conversational AI to enhance tone of voice and communication strategies.

He also highlights the rapid advancements in AI technology and the potential for autonomous AI agents. Luke concludes by inviting brands to explore the possibilities of using conversational AI to differentiate their communication approach.

Takeaways

• Conversational AI can be used to enhance public relations and communications strategies.
• Understanding use cases and leveraging AI to enhance tone of voice is crucial.
• Rapid advancements in AI technology are opening up new possibilities.
• The future may involve the use of autonomous AI agents in communication.

Chapters

• 00:00 Introduction and Overview
• 01:31 The Impact of Generative AI on the Company
• 04:35 Initial Use of AI and its Evolution
• 06:17 The Excitement and Challenges of AI in the Industry
• 08:59 The Future of AI in Agencies and Businesses
• 11:35 The Human Dimension in AI Development
• 14:14 The Need for More Resources in AI Development
• 18:47 The Role of Humans in AI-Assisted Communication
• 21:58 The Impact of AI on Society and Government
• 23:59 The Future of Conversational AI in Communication
• 24:57 Using Conversational AI to Improve Communication Strategies
• 27:20 The Importance of Language and Tone of Voice in Conversational AI
• 29:06 Contact Information and Conclusion